Search

The Trans-Iron Galactic Element Recorder (TIGER) family of instruments is optimized to measure the relative abundances of the rare, ultra-heavy galactic cosmic rays (UHGCRs) with atomic number (Z) Z ≥ 30. Observing the UHGCRs places a premium on exposure that the balloon-borne SuperTIGER achieved with a large area detector (5.6 m2) and two Antarctic flights totaling 87 days, while the smaller (∼1 m2) TIGER for the International Space Station (TIGERISS) aims to achieve this with a longer observation time from one to several years. SuperTIGER uses a combination of scintillator and Cherenkov detectors to determine charge and energy. TIGERISS will use silicon strip detectors (SSDs) instead of scintillators, with improved charge resolution, signal linearity, and dynamic range. Extended single-element resolution UHGCR measurements through 82Pb will cover elements produced in s-process and r-process neutron capture nucleosynthesis, adding to the multi-messenger effort to determine the relative contributions of supernovae (SNe) and Neutron Star Merger (NSM) events to the r-process nucleosynthesis product content of the galaxy.

Abstract Variability in response to short-acting β2-agonists (e.g., albuterol) among patients with asthma from diverse racial/ethnic groups may contribute to asthma disparities. We sought to identify genetic variants associated with bronchodilator response (BDR) to identify potential mechanisms of drug response and risk factors for worse asthma outcomes. Genome-wide association studies of bronchodilator response (BDR) were performed using TOPMed Whole Genome Sequencing data of the Asthma Translational Genomic Collaboration (ATGC), which corresponded to 1136 Puerto Rican, 656 Mexican and 4337 African American patients with asthma. With the population-specific GWAS results, a trans-ethnic meta-analysis was performed to identify BDR-associated variants shared across the three populations. Replication analysis was carried out in three pediatric asthma cohorts, including CAMP (Childhood Asthma Management Program; n = 560), GACRS (Genetics of Asthma in Costa Rica Study; n = 967) and HPR (Hartford-Puerto Rico; n = 417). A genome-wide significant locus (rs35661809; P = 3.61 × 10–8) in LINC02220, a non-coding RNA gene, was identified in Puerto Ricans. While this region was devoid of protein-coding genes, capture Hi-C data showed a distal interaction with the promoter of the DNAH5 gene in lung tissue. In replication analysis, the GACRS cohort yielded a nominal association (1-tailed P

Emission of organic aerosol (OA) from wood combustion is not well constrained; understanding the governing factors of OA emissions would aid in explaining the reported variability. Pyrolysis of the wood during combustion is the process that produces and releases OA precursors. We performed controlled pyrolysis experiments at representative combustion conditions. The conditions changed were the temperature, wood length, wood moisture content, and wood type. The mass loss of the wood, the particle concentrations, and light-gas concentrations were measured continuously. The experiments were repeatable as shown by a single experiment, performed nine times, in which the real-time particle concentration varied by a maximum of 20 %. Higher temperatures increased the mass loss rate and the released concentration of gases and particles. Large wood size had a lower yield of particles than the small size because of higher mass transfer resistance. Reactions outside the wood became important between 500 and 600 ∘C. Elevated moisture content reduced product formation because heat received was shared between pyrolysis reactions and moisture evaporation. The thermophysical properties, especially the thermal diffusivity, of wood controlled the difference in the mass loss rate and emission among seven wood types. This work demonstrates that OA emission from wood pyrolysis is a deterministic process that depends on transport phenomena.

The organic mass fraction from sea spray aerosol (SSA) is currently a subject of intense research. The majority of this research is dedicated to measurements in ambient air. However a number of studies have recently started to focus on nascent sea spray aerosol. This work presents measurements collected during a 5-week cruise in May and June 2017 in the central and western Mediterranean Sea, an oligotrophic marine region with low phytoplankton biomass. Surface seawater was continuously pumped into a bubble-bursting apparatus to generate nascent sea spray aerosol. Size distributions were measured with a differential mobility particle sizer (DMPS). Chemical characterization of the submicron aerosol was performed with a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) operating with 10 min time resolution and with filter-based chemical analysis on a daily basis. Using positive matrix factorization analysis, the ToF-ACSM non-refractory organic matter (OMNR) was separated into four different organic aerosol types, identified as primary OA (POANR), oxidized OA (OOANR), methanesulfonic acid type OA (MSA-OANR), and mixed OA (MOANR). In parallel, surface seawater biogeochemical properties were monitored providing information on phytoplankton cell abundance and seawater particulate organic carbon (1 h time resolution) and seawater surface microlayer (SML) dissolved organic carbon (DOC) (on a daily basis). Statistically robust correlations (for n>500) were found between MOANR and nanophytoplankton cell abundance, as well as between POANR, OOANR, and particulate organic carbon (POC). Parameterizations of the contributions of different types of organics to the submicron nascent sea spray aerosol are proposed as a function of the seawater biogeochemical properties for use in models.

In this work, Meisenheimer et al. use careful epitaxial growth of FeGa thin films to achieve a metastable state with remarkably high magetostrictive coefficients. Materials with strong magnetostrictive properties are vital components in magnetoelectric multiferroic heterostructures, with considerable potential for use a variety of technologies.

Oxidation flow reactors (OFRs) are an emerging tool for studying the formation and oxidative aging of organic aerosols and other applications. The majority of OFR studies to date have involved the generation of the hydroxyl radical (OH) to mimic daytime oxidative aging processes. In contrast, the use of the nitrate radical (NO3) in modern OFRs to mimic nighttime oxidative aging processes has been limited due to the complexity of conventional techniques that are used to generate NO3. Here, we present a new method that uses a laminar flow reactor (LFR) to continuously generate dinitrogen pentoxide (N2O5) in the gas phase at room temperature from the NO2 + O3 and NO2 + NO3 reactions. The N2O5 is then injected into a dark Potential Aerosol Mass (PAM) OFR and decomposes to generate NO3; hereafter, this method is referred to as “OFR-iN2O5” (where “i” stands for “injected”). To assess the applicability of the OFR-iN2O5 method towards different chemical systems, we present experimental and model characterization of the integrated NO3 exposure, NO3:O3, NO2:NO3, and NO2:O2 as a function of LFR and OFR conditions. These parameters were used to investigate the fate of representative organic peroxy radicals (RO2) and aromatic alkyl radicals generated from volatile organic compound (VOC) + NO3 reactions, and VOCs that are reactive towards both O3 and NO3. Finally, we demonstrate the OFR-iN2O5 method by generating and characterizing secondary organic aerosol from the β-pinene + NO3 reaction.

Abstract Background Prior research suggests that substance use disorders (SUDs) are associated with risk of suicide mortality, but most previous work has been conducted among Veterans Health Administration patients. Few studies have examined the relationship between SUDs and suicide mortality in general populations. Our study estimates the association of SUDs with suicide mortality in a general US population of men and women who receive care across eight integrated health systems. Methods We conducted a case–control study using electronic health records and claims data from eight integrated health systems of the Mental Health Research Network. Participants were 2674 men and women who died by suicide between 2000–2013 and 267,400 matched controls. The main outcome was suicide mortality, assessed using data from the health systems and confirmed by state death data systems. Demographic and diagnostic data on substance use disorders and other health conditions were obtained from each health system. First, we compared descriptive statistics for cases and controls, including age, gender, income, and education. Next, we compared the rate of each substance use disorder category for cases and controls. Finally, we used conditional logistic regression models to estimate unadjusted and adjusted odds of suicide associated with each substance use disorder category. Results All categories of substance use disorders were associated with increased risk of suicide mortality. Adjusted odds ratios ranged from 2.0 (CI 1.7, 2.3) for patients with tobacco use disorder only to 11.2 (CI 8.0, 15.6) for patients with multiple alcohol, drug, and tobacco use disorders. Substance use disorders were associated with increased relative risk of suicide for both women and men across all categories, but the relative risk was more pronounced in women. Conclusions Substance use disorders are associated with significant risk of suicide mortality, especially for women, even after controlling for other important risk factors. Experiencing multiple substance use disorders is particularly risky. These findings suggest increased suicide risk screening and prevention efforts for individuals with substance use disorders are needed.

Magnetic resonance elastography (MRE) is an MRI technique for imaging the mechanical properties of brain in vivo, and has shown differences in properties between neuroanatomical regions and sensitivity to aging, neurological disorders, and normal brain function. Past MRE studies investigating these properties have typically assumed the brain is mechanically isotropic, though the aligned fibers of white matter suggest an anisotropic material model should be considered for more accurate parameter estimation. Here we used a transversely isotropic, nonlinear inversion algorithm (TI-NLI) and multi-excitation MRE to estimate the anisotropic material parameters of individual white matter tracts in healthy young adults. We found significant differences between individual tracts for three recovered anisotropic parameters: substrate shear stiffness, μ (range: 2.57 – 3.02 kPa), shear anisotropy, φ (range: -0.026 – 0.164), and tensile anisotropy, ζ (range: 0.559 – 1.049). Additionally, we demonstrated the repeatability of these parameter estimates in terms of lower variability of repeated measures in a single subject relative to variability in our sample population. Further, we observed significant differences in anisotropic mechanical properties between segments of the corpus callosum (genu, body, and splenium), which is expected based on differences in axonal microstructure. This study shows the ability of MRE with TI-NLI to estimate anisotropic mechanical properties of white matter and presents reference properties for tracts throughout the healthy brain. Statement of significance: In this study we use magnetic resonance elastography to determine the mechanical properties of white matter, which can be useful in characterizing neurological conditions such as multiple sclerosis and traumatic brain injury. However, due to its fibrous nature, accurate estimation of mechanical properties of white matter requires an anisotropic material model. In this work, we use a transversely isotropic inversion algorithm with data from multi-excitation MRE to determine the anisotropic mechanical properties of white matter in a healthy young population based upon an anisotropic material model. We display the ability of MRE to capture structural differences between different white matter tracts and sub-regions of these tracts, which are expected to reflect differences such as average axon thickness and myelin density. This robust estimation of white matter anisotropic properties in a young, healthy population provides an avenue for future studies to implement these methods to examine brain development, aging, and pathology.

Summary: Genetic studies on telomere length are important for understanding age-related diseases. Prior GWASs for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally diverse individuals (European, African, Asian, and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole-genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n = 109,122 individuals. We identified 59 sentinel variants (p < 5 × 10−9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated that the independent signals colocalized with cell-type-specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated that our TL polygenic trait scores (PTSs) were associated with an increased risk of cancer-related phenotypes.

Objective. The concentrations of endogenous metabolites in saliva can be altered based on the systemic condition of the hosts and may, in theory, serve as a reflection of systemic disease progression. Hemoglobin A1C is used clinically to measure long-term average glycemic control. The aim of the study was to demonstrate if there were differences in the salivary metabolic profiles between well and poorly controlled type 1 and type 2 subjects with diabetes. Subjects and Methods. Subjects with type 1 and type 2 diabetes were enrolled (n = 40). The subjects were assigned to phenotypic groups based on their current level of A1C: 7 = poorly controlled. Demographic data, age, gender, and ethnicity, were used to match the two phenotypic groups. Whole saliva samples were collected and immediately stored at −80°C. Samples were spiked using an isotopically labeled internal standard and analyzed by UPLC-TOF-MS using a Waters SYNAPT G2-Si mass spectrometer. Results. Unsupervised principal components analysis (PCA) and orthogonal partial least squares regression discrimination analysis (OPLS-DA) were used to define unique metabolomic profiles associated with well and poorly controlled diabetes based on A1C levels. Conclusion. OPLS-DA demonstrates good separation of well and poorly controlled in both type 1 and type 2 diabetes. This provides evidence for developing saliva-based monitoring tools for diabetes.

An air-to-air ultrafine particle concentrator (Aerosol Dynamics Inc. concentrator; ADIc) has been designed to enhance online chemical characterization of ambient aerosols using aerosol mass spectrometry. The ADIc employs a three-stage, moderated water-based condensation growth tube coupled to an aerodynamic focusing nozzle to concentrate fine particles into a portion of the flow. The system can be configured to sample between 1.0 and 1.7 L min−1, with an output concentrated flow between 0.08 and 0.12 L min−1, resulting in a theoretical concentration factor (sample flow / output flow) ranging from 8 to 21. Laboratory tests with monodisperse particles show that the ADIc is effective for particles as small as 10 nm. Laboratory experiments conducted with the Aerosol Mass Spectrometer (AMS) showed no shift in the particle size with the ADIc, as measured by the AMS particle time-of-flight operation. The ADIc-AMS system was operated unattended over a 1-month period near Boston, Massachusetts. Comparison to a parallel AMS without the concentrator showed concentration factors of 9.7±0.15 and 9.1±0.1 for sulfate and nitrate, respectively, when operated with a theoretical concentration factor of 10.5±0.3. The concentration factor of organics was lower, possibly due to the presence of large particles from nearby road-paving operations and a difference in aerodynamic lens cutoff between the two AMS instruments. Another field deployment was carried out in Helsinki, Finland. Two ∼10 d measurement periods showed good correlation for the concentrations of organics, sulfate, nitrate and ammonium measured with an Aerosol Chemical Speciation Monitor (ACSM) with the ADIc and a parallel AMS without the concentrator. Additional experiments with an AMS alternating between the ADIc and a bypass line demonstrated that the concentrator did not significantly change the size distribution or the chemistry of the ambient aerosol particles.

The burden of asthma varies between ancestries, but GWAS have so far focused on mainly European ancestry populations. Here, Daya et al. perform GWAS for asthma in 14,654 individuals of African ancestry and, besides confirming previously known loci, identify two potentially African ancestry-specific loci.

Introduction Global shortages in the supply of SARS-CoV-2 vaccines have resulted in campaigns to first inoculate individuals at highest risk for death from COVID-19. Here, we develop a predictive model of COVID-19-related death using longitudinal clinical data from patients in metropolitan Detroit.Methods All individuals included in the analysis had a laboratory-confirmed SARS-CoV-2 infection. Thirty-six pre-existing conditions with a false discovery rate p

We provide an analysis and statement of the source term in the classical Kaluza field equations, by considering the 5-dimensional (5D) energy-momentum tensor corresponding to the 5D geodesic hypothesis that is typically presumed in the Kaluza theory. By providing the 5D matter Lagrangian, this work completes a Lagrangian analysis of the classical Kaluza theory that began by establishing the proper form of the unique Kaluza field Lagrangian. This work considers the transformation properties necessitated by general covariance of the Kaluza source terms, to establish the correct form for the source terms in the field equations, and to establish the 5D matter Lagrangian that corresponds to the 5D geodesic hypothesis. In addition to the effects of a scalar field expected from other scalar-tensor or scalar-electromagnetic theories, a peculiar Kaluza coupling coefficient arises for charged matter which acts to vary the source strengths in ways unknown to conventional physics. We briefly evaluate the implied modifications to source terms in the field equations. We find an ADM-like neutralization of gravity at high specific charge states and a saturation in field strength at high specific charge-to-mass ratios.

We present new results regarding the long-range scalar field that emerges from the classical Kaluza unification of general relativity and electromagnetism. The Kaluza framework reproduces known physics exactly when the scalar field goes to one, so we studied perturbations of the scalar field around unity, as is done for gravity in the Newtonian limit of general relativity. A suite of interesting phenomena unknown to the Kaluza literature is revealed: planetary masses are clothed in scalar field, which contributes 25% of the mass-energy of the clothed mass; the scalar potential around a planet is positive, compared with the negative gravitational potential; at laboratory scales, the scalar charge which couples to the scalar field is quadratic in electric charge; a new length scale of physics is encountered for the static scalar field around an electrically-charged mass, Ls=μ0Q2/M; the scalar charge of elementary particles is proportional to the electric charge, making the scalar force indistinguishable from the atomic electric force. An unduly strong electrogravitic buoyancy force is predicted for electrically-charged objects in the planetary scalar field, and this calculation appears to be the first quantitative falsification of the Kaluza unification. Since the simplest classical field, a long-range scalar field, is expected in nature, and since the Kaluza scalar field is as weak as gravity, we suggest that if there is an error in this calculation, it is likely to be in the magnitude of the coupling to the scalar field, not in the existence or magnitude of the scalar field itself.

BackgroundMitochondria support critical cellular functions, such as energy production through oxidative phosphorylation, regulation of reactive oxygen species, apoptosis, and calcium homeostasis.ObjectiveGiven the heightened level of cellular activity in patients with asthma, we sought to determine whether mitochondrial DNA (mtDNA) copy number measured in peripheral blood differed between individuals with and without asthma.MethodsWhole genome sequence data was generated as part of the Trans-Omics for Precision Medicine (TOPMed) Program on participants from the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) and the Study of African Americans, Asthma, Genes, & Environment II (SAGE II). We restricted our analysis to individuals who self-identified as African American (3,651 asthma cases and 1,344 controls). Mitochondrial copy number was estimated using the sequencing read depth ratio for the mitochondrial and nuclear genomes. Respiratory complex expression was assessed using RNA-sequencing.ResultsAverage mitochondrial copy number was significantly higher among individuals with asthma when compared with controls (SAPPHIRE: 218.60 vs. 200.47, PConclusionsWe observed a robust association between asthma and higher mitochondrial copy number. Asthma having an effect on mitochondria function was also supported by lower respiratory complex gene expression in this group.

Pulmonary function is influenced by environmental factors, lifestyle, and genetics. Here, in a multiethnic GWAS meta-analysis for pulmonary function traits, the authors identify over 50 additional genetic loci, a subset of which are specific for European, African, Asian, or Hispanic/Latino ancestry.

Anteroposterior axis extension during gastrulation is dynamically coordinated, but how this is regulated at a molecular level is unclear. Here, the authors show in zebrafish that the chromatin factor Gon4l, encoded by ugly duckling, coordinates axis extension by modulating EpCAM and Integrinα3b expression.

Evidence is accumulating that emissions of primary particulate matter (PM) from residential wood and coal combustion in the UK may be underestimated and/or spatially misclassified. In this study, different assumptions for the spatial distribution and total emission of PM from solid fuel (wood and coal) burning in the UK were tested using an atmospheric chemical transport model. Modelled concentrations of the PM components were compared with measurements from aerosol mass spectrometers at four sites in central and Greater London (ClearfLo campaign, 2012), as well as with measurements from the UK black carbon network.The two main alternative emission scenarios modelled were Base4x and combRedist. For Base4x, officially reported PM2.5 from the residential and other non-industrial combustion source sector were increased by a factor of four. For the combRedist experiment, half of the baseline emissions from this same source were redistributed by residential population density to simulate the effect of allocating some emissions to the smoke control areas (that are assumed in the national inventory to have no emissions from this source). The Base4x scenario yielded better daily and hourly correlations with measurements than the combRedist scenario for year-long comparisons of the solid fuel organic aerosol (SFOA) component at the two London sites. However, the latter scenario better captured mean measured concentrations across all four sites. A third experiment, Redist – all emissions redistributed linearly to population density, is also presented as an indicator of the maximum concentrations an assumption like this could yield.The modelled elemental carbon (EC) concentrations derived from the combRedist experiments also compared well with seasonal average concentrations of black carbon observed across the network of UK sites. Together, the two model scenario simulations of SFOA and EC suggest both that residential solid fuel emissions may be higher than inventory estimates and that the spatial distribution of residential solid fuel burning emissions, particularly in smoke control areas, needs re-evaluation. The model results also suggest the assumed temporal profiles for residential emissions may require review to place greater emphasis on evening (including discretionary) solid fuel burning.

Arctic, Antarctic and alpine biological soil crusts (BSCs) are formed by adhesion of soil particles to exopolysaccharides (EPSs) excreted by cyanobacterial and green algal communities, the pioneers and main primary producers in these habitats. These BSCs provide and influence many ecosystem services such as soil erodibility, soil formation and nitrogen (N) and carbon (C) cycles. In cold environments degradation rates are low and BSCs continuously increase soil organic C; therefore, these soils are considered to be CO2 sinks. This work provides a novel, non-destructive and highly comparable method to investigate intact BSCs with a focus on cyanobacteria and green algae and their contribution to soil organic C. A new terminology arose, based on confocal laser scanning microscopy (CLSM) 2-D biomaps, dividing BSCs into a photosynthetic active layer (PAL) made of active photoautotrophic organisms and a photosynthetic inactive layer (PIL) harbouring remnants of cyanobacteria and green algae glued together by their remaining EPSs. By the application of CLSM image analysis (CLSM–IA) to 3-D biomaps, C coming from photosynthetic active organisms could be visualized as depth profiles with C peaks at 0.5 to 2 mm depth. Additionally, the CO2 sink character of these cold soil habitats dominated by BSCs could be highlighted, demonstrating that the first cubic centimetre of soil consists of between 7 and 17 % total organic carbon, identified by loss on ignition.

There is a drag force on objects moving in the background cosmological metric, known from galaxy cluster dynamics. The force is quite small over laboratory timescales, yet it applies in principle to all moving bodies in the universe. The drag force can be understood as inductive rectilinear frame dragging because it also exists in the rest frame of a moving object, and it arises in that frame from the off-diagonal components induced in the boosted-frame metric. Unlike the Kerr metric or other typical frame-dragging geometries, cosmological inductive dragging occurs at uniform velocity, along the direction of motion, and dissipates energy. Proposed gravito-magnetic invariants formed from contractions of the Riemann tensor do not capture inductive dragging effects, and this might be the first identification of inductive rectilinear dragging. The existence of this drag force proves it is possible for matter in motion through a finite region to exchange momentum and energy with the gravitational field of the universe. The cosmological metric can in principle be determined through this force from local measurements on moving bodies, at resolutions similar to that of the Pound–Rebka experiment.

The SAFIRED (Savannah Fires in the Early Dry Season) campaign took place from 29 May until 30 June 2014 at the Australian Tropical Atmospheric Research Station (ATARS) in the Northern Territory, Australia. The purpose of this campaign was to investigate emissions from fires in the early dry season in northern Australia. Measurements were made of biomass burning aerosols, volatile organic compounds, polycyclic aromatic carbons, greenhouse gases, radon, speciated atmospheric mercury and trace metals. Aspects of the biomass burning aerosol emissions investigated included; emission factors of various species, physical and chemical aerosol properties, aerosol aging, micronutrient supply to the ocean, nucleation, and aerosol water uptake. Over the course of the month-long campaign, biomass burning signals were prevalent and emissions from several large single burning events were observed at ATARS.Biomass burning emissions dominated the gas and aerosol concentrations in this region. Dry season fires are extremely frequent and widespread across the northern region of Australia, which suggests that the measured aerosol and gaseous emissions at ATARS are likely representative of signals across the entire region of north Australia. Air mass forward trajectories show that these biomass burning emissions are carried north-west over the Timor Sea and could influence the atmosphere over Indonesia and the tropical atmosphere over the Indian Ocean. Here we present characteristics of the biomass burning observed at the sampling site and provide an overview of the more specific outcomes of the SAFIRED campaign.

The environments in which we live, work, and play are subject to enormous variability in air pollutant concentrations. To adequately characterize air quality (AQ), measurements must be fast (real time), scalable, and reliable (with known accuracy, precision, and stability over time). Lower-cost air-quality-sensor technologies offer new opportunities for fast and distributed measurements, but a persistent characterization gap remains when it comes to evaluating sensor performance under realistic environmental sampling conditions. This limits our ability to inform the public about pollution sources and inspire policy makers to address environmental justice issues related to air quality. In this paper, initial results obtained with a recently developed lower-cost air-quality-sensor system are reported. In this project, data were acquired with the ARISense integrated sensor package over a 4.5-month time interval during which the sensor system was co-located with a state-operated (Massachusetts, USA) air quality monitoring station equipped with reference instrumentation measuring the same pollutant species. This paper focuses on validating electrochemical (EC) sensor measurements of CO, NO, NO2, and O3 at an urban neighborhood site with pollutant concentration ranges (parts per billion by volume, ppb; 5 min averages, ±1σ): [CO] = 231 ± 116 ppb (spanning 84–1706 ppb), [NO] = 6.1 ± 11.5 ppb (spanning 0–209 ppb), [NO2] = 11.7 ± 8.3 ppb (spanning 0–71 ppb), and [O3] = 23.2 ± 12.5 ppb (spanning 0–99 ppb). Through the use of high-dimensional model representation (HDMR), we show that interference effects derived from the variable ambient gas concentration mix and changing environmental conditions over three seasons (sensor flow-cell temperature = 23.4 ± 8.5 °C, spanning 4.1 to 45.2 °C; and relative humidity = 50.1 ± 15.3 %, spanning 9.8–79.9 %) can be effectively modeled for the Alphasense CO-B4, NO-B4, NO2-B43F, and Ox-B421 sensors, yielding (5 min average) root mean square errors (RMSE) of 39.2, 4.52, 4.56, and 9.71 ppb, respectively. Our results substantiate the potential for distributed air pollution measurements that could be enabled with these sensors.

Abstract Background A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic. Results The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes. Conclusions This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

The vast majority of Australia's fires occur in the tropical north of the continent during the dry season. These fires are a significant source of aerosol and cloud condensation nuclei (CCN) in the region, providing a unique opportunity to investigate the biomass burning aerosol (BBA) in the absence of other sources. CCN concentrations at 0.5 % supersaturation and aerosol size and chemical properties were measured at the Australian Tropical Atmospheric Research Station (ATARS) during June 2014. CCN concentrations reached over 104 cm−3 when frequent and close fires were burning – up to 45 times higher than periods with no fires. Both the size distribution and composition of BBA appeared to significantly influence CCN concentrations. A distinct diurnal trend in the proportion of BBA activating to cloud droplets was observed, with an activation ratio of 40 ± 20 % during the night and 60 ± 20 % during the day. BBA was, on average, less hygroscopic during the night (κ = 0. 04 ± 0.03) than during the day (κ = 0.07 ± 0.05), with a maximum typically observed just before midday. Size-resolved composition of BBA showed that organics comprised a constant 90 % of the aerosol volume for aerodynamic diameters between 100 and 200 nm. While this suggests that the photochemical oxidation of organics led to an increase in the hygroscopic growth and an increase in daytime activation ratios, it does not explain the decrease in hygroscopicity after midday. Modelled CCN concentrations assuming typical continental hygroscopicities produced very large overestimations of up to 200 %. Smaller, but still significant, overpredictions up to ∼ 100 % were observed using aerosol mass spectrometer (AMS)- and hygroscopicity tandem differential mobility analyser (H-TDMA)-derived hygroscopicities as well as campaign night and day averages. The largest estimations in every case occurred during the night, when the small variations in very weakly hygroscopic species corresponded to large variations in the activation diameters. Trade winds carry the smoke generated from these fires over the Timor Sea, where aerosol–cloud interactions are likely to be sensitive to changes in CCN concentrations, perturbing cloud albedo and lifetime. Dry season fires in northern Australia are therefore potentially very important in cloud processes in this region.

There is a lack of knowledge of how biomass burning aerosols in the tropics age, including those in the fire-prone Northern Territory in Australia. This paper reports chemical characterization of fresh and aged aerosols monitored during the 1-month-long SAFIRED (Savannah Fires in the Early Dry Season) field study, with an emphasis on the chemical signature and aging of organic aerosols. The campaign took place in June 2014 during the early dry season when the surface measurement site, the Australian Tropical Atmospheric Research Station (ATARS), located in the Northern Territory, was heavily influenced by thousands of wild and prescribed bushfires. ATARS was equipped with a wide suite of instrumentation for gaseous and aerosol characterization. A compact time-of-flight aerosol mass spectrometer was deployed to monitor aerosol chemical composition. Approximately 90 % of submicron non-refractory mass was composed of organic material. Ozone enhancement in biomass burning plumes indicated increased air mass photochemistry. The diversity in biomass burning emissions was illustrated through variability in chemical signature (e.g. wide range in f44, from 0.06 to 0.18) for five intense fire events. The background particulate loading was characterized using positive matrix factorization (PMF). A PMF-resolved BBOA (biomass burning organic aerosol) factor comprised 24 % of the submicron non-refractory organic aerosol mass, confirming the significance of fire sources. A dominant PMF factor, OOA (oxygenated organic aerosol), made up 47 % of the sampled aerosol, illustrating the importance of aerosol aging in the Northern Territory. Biogenic isoprene-derived organic aerosol factor was the third significant fraction of the background aerosol (28 %).

Oyster diseases are a major impediment to the profitability and growth of the oyster aquaculture industry. In recent years, geographically widespread outbreaks of disease caused by ostreid herpesvirus-1 microvariant (OsHV-1 μvar) have led to mass mortalities among Crassostrea gigas, the Pacific Oyster. Attempts to minimize the impact of this disease have been largely focused on breeding programs, and although these have shown some success in producing oyster families with reduced mortality, the mechanism(s) behind this protection is poorly understood. One possible factor is modification of the C. gigas microbiome. To explore how breeding for resistance to OsHV-1 μvar affects the oyster microbiome, we used 16S rRNA amplicon sequencing to characterize the bacterial communities associated with 35 C. gigas families, incorporating oysters with different levels of susceptibility to OsHV-1 μvar disease. The microbiomes of disease-susceptible families were significantly different to the microbiomes of disease-resistant families. OTUs assigned to the Photobacterium, Vibrio, Aliivibrio, Streptococcus, and Roseovarius genera were associated with low disease resistance. In partial support of this finding, qPCR identified a statistically significant increase of Vibrio-specific 16S rRNA gene copies in the low disease resistance families, possibly indicative of a reduced host immune response to these pathogens. In addition to these results, examination of the core microbiome revealed that each family possessed a small core community, with OTUs assigned to the Winogradskyella genus and the Bradyrhizobiaceae family consistent members across most disease-resistant families. This study examines patterns in the microbiome of oyster families exhibiting differing levels of OsHV-1 μvar disease resistance and reveals some key bacterial taxa that may provide a protective or detrimental role in OsHV-1 μvar disease outbreaks.

The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) aims to better understand population genetics of the African diaspora. Here, it uses deeply sequenced whole-genomes to describe the impact of admixture and potential disease burden of deleterious variants.

Personalized medicine requires accurate and ethnicity-optimized reference genome panels. Here, the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) evaluates typical variant filters and existing genome databases against newly sequenced African-ancestry populations.

We present high-resolution (5 km × 5 km) atmospheric chemical transport model (ACTM) simulations of the impact of newly estimated traffic-related emissions on secondary organic aerosol (SOA) formation over the UK for 2012. Our simulations include additional diesel-related intermediate-volatility organic compound (IVOC) emissions derived directly from comprehensive field measurements at an urban background site in London during the 2012 Clean Air for London (ClearfLo) campaign. Our IVOC emissions are added proportionally to VOC emissions, as opposed to proportionally to primary organic aerosol (POA) as has been done by previous ACTM studies seeking to simulate the effects of these missing emissions. Modelled concentrations are evaluated against hourly and daily measurements of organic aerosol (OA) components derived from aerosol mass spectrometer (AMS) measurements also made during the ClearfLo campaign at three sites in the London area. According to the model simulations, diesel-related IVOCs can explain on average ∼ 30 % of the annual SOA in and around London. Furthermore, the 90th percentile of modelled daily SOA concentrations for the whole year is 3.8 µg m−3, constituting a notable addition to total particulate matter. More measurements of these precursors (currently not included in official emissions inventories) is recommended. During the period of concurrent measurements, SOA concentrations at the Detling rural background location east of London were greater than at the central London location. The model shows that this was caused by an intense pollution plume with a strong gradient of imported SOA passing over the rural location. This demonstrates the value of modelling for supporting the interpretation of measurements taken at different sites or for short durations.

The composition of PM1 (particulate matter with diameter less than 1 µm) in the greater London area was characterized during the Clean Air for London (ClearfLo) project in winter 2012. Two high-resolution time-of-flight aerosol mass spectrometers (HR-ToF-AMS) were deployed at a rural site (Detling, Kent) and an urban site (North Kensington, London). The simultaneous and high-temporal resolution measurements at the two sites provide a unique opportunity to investigate the spatial distribution of PM1. We find that the organic aerosol (OA) concentration is comparable between the rural and urban sites, but the contribution from different sources is distinctly different between the two sites. The concentration of solid fuel OA at the urban site is about twice as high as at the rural site, due to elevated domestic heating in the urban area. While the concentrations of oxygenated OA (OOA) are well-correlated between the two sites, the OOA concentration at the rural site is almost twice that of the urban site. At the rural site, more than 70 % of the carbon in OOA is estimated to be non-fossil, which suggests that OOA is likely related to aged biomass burning considering the small amount of biogenic SOA in winter. Thus, it is possible that the biomass burning OA contributes a larger fraction of ambient OA in wintertime than what previous field studies have suggested. A suite of instruments was deployed downstream of a thermal denuder (TD) to investigate the volatility of PM1 species at the rural Detling site. After heating at 250 °C in the TD, 40 % of the residual mass is OA, indicating the presence of non-volatile organics in the aerosol. Although the OA associated with refractory black carbon (rBC; measured by a soot-particle aerosol mass spectrometer) only accounts for

BackgroundIt remains unclear whether beta‐blockade is similarly effective in black patients with heart failure and reduced ejection fraction as in white patients, but self‐reported race is a complex social construct with both biological and environmental components. The objective of this study was to compare the reduction in mortality associated with beta‐blocker exposure in heart failure and reduced ejection fraction patients by both self‐reported race and by proportion African genetic ancestry. Methods and ResultsInsured patients with heart failure and reduced ejection fraction (n=1122) were included in a prospective registry at Henry Ford Health System. This included 575 self‐reported blacks (129 deaths, 22%) and 547 self‐reported whites (126 deaths, 23%) followed for a median 3.0 years. Beta‐blocker exposure (BBexp) was calculated from pharmacy claims, and the proportion of African genetic ancestry was determined from genome‐wide array data. Time‐dependent Cox proportional hazards regression was used to separately test the association of BBexp with all‐cause mortality by self‐reported race or by proportion of African genetic ancestry. Both sets of models were evaluated unadjusted and then adjusted for baseline risk factors and beta‐blocker propensity score. BBexp effect estimates were protective and of similar magnitude both by self‐reported race and by African genetic ancestry (adjusted hazard ratio=0.56 in blacks and adjusted hazard ratio=0.48 in whites). The tests for interactions with BBexp for both self‐reported race and for African genetic ancestry were not statistically significant in any model (P>0.1 for all). ConclusionsAmong black and white patients with heart failure and reduced ejection fraction, reduction in all‐cause mortality associated with BBexp was similar, regardless of self‐reported race or proportion African genetic ancestry.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Trace element measurements in PM10–2.5, PM2.5–1.0 and PM1.0–0.3 aerosol were performed with 2 h time resolution at kerbside, urban background and rural sites during the ClearfLo winter 2012 campaign in London. The environment-dependent variability of emissions was characterized using the Multilinear Engine implementation of the positive matrix factorization model, conducted on data sets comprising all three sites but segregated by size. Combining the sites enabled separation of sources with high temporal covariance but significant spatial variability. Separation of sizes improved source resolution by preventing sources occurring in only a single size fraction from having too small a contribution for the model to resolve. Anchor profiles were retrieved internally by analysing data subsets, and these profiles were used in the analyses of the complete data sets of all sites for enhanced source apportionment. A total of nine different factors were resolved (notable elements in brackets): in PM10–2.5, brake wear (Cu, Zr, Sb, Ba), other traffic-related (Fe), resuspended dust (Si, Ca), sea/road salt (Cl), aged sea salt (Na, Mg) and industrial (Cr, Ni); in PM2.5–1.0, brake wear, other traffic-related, resuspended dust, sea/road salt, aged sea salt and S-rich (S); and in PM1.0–0.3, traffic-related (Fe, Cu, Zr, Sb, Ba), resuspended dust, sea/road salt, aged sea salt, reacted Cl (Cl), S-rich and solid fuel (K, Pb). Human activities enhance the kerb-to-rural concentration gradients of coarse aged sea salt, typically considered to have a natural source, by 1.7–2.2. These site-dependent concentration differences reflect the effect of local resuspension processes in London. The anthropogenically influenced factors traffic (brake wear and other traffic-related processes), dust and sea/road salt provide further kerb-to-rural concentration enhancements by direct source emissions by a factor of 3.5–12.7. The traffic and dust factors are mainly emitted in PM10–2.5 and show strong diurnal variations with concentrations up to 4 times higher during rush hour than during night-time. Regionally influenced S-rich and solid fuel factors, occurring primarily in PM1.0–0.3, have negligible resuspension influences, and concentrations are similar throughout the day and across the regions.

Ambient concentrations of trace elements with 2 h time resolution were measured in PM10–2.5, PM2.5–1.0 and PM1.0–0.3 size ranges at kerbside, urban background and rural sites in London during winter 2012. Samples were collected using rotating drum impactors (RDIs) and subsequently analysed with synchrotron radiation-induced X-ray fluorescence spectrometry (SR-XRF). Quantification of kerb and urban increments (defined as kerb-to-urban and urban-to-rural concentration ratios, respectively), and assessment of diurnal and weekly variability provided insight into sources governing urban air quality and the effects of urban micro-environments on human exposure. Traffic-related elements yielded the highest kerb increments, with values in the range of 10.4 to 16.6 for SW winds (3.3–6.9 for NE) observed for elements influenced by brake wear (e.g. Cu, Sb, Ba) and 5.7 to 8.2 for SW (2.6–3.0 for NE) for other traffic-related processes (e.g. Cr, Fe, Zn). Kerb increments for these elements were highest in the PM10–2.5 mass fraction, roughly twice that of the PM1.0–0.3 fraction. These elements also showed the highest urban increments (~ 3.0), although no difference was observed between brake wear and other traffic-related elements. All elements influenced by traffic exhibited higher concentrations during morning and evening rush hours, and on weekdays compared to weekends, with the strongest trends observed at the kerbside site, and additionally enhanced by winds coming directly from the road, consistent with street canyon effects. Elements related to mineral dust (e.g. Al, Si, Ca, Sr) showed significant influences from traffic-induced resuspension, as evidenced by moderate kerb (3.4–5.4 for SW, 1.7–2.3 for NE) and urban (~ 2) increments and increased concentrations during peak traffic flow. Elements related to regional transport showed no significant enhancement at kerb or urban sites, with the exception of PM10–2.5 sea salt (factor of up to 2), which may be influenced by traffic-induced resuspension of sea and/or road salt. Heavy-duty vehicles appeared to have a larger effect than passenger vehicles on the concentrations of all elements influenced by resuspension (including sea salt) and wearing processes. Trace element concentrations in London were influenced by both local and regional sources, with coarse and intermediate fractions dominated by traffic-induced resuspension and wearing processes and fine particles influenced by regional transport.

Elemental compositions of organic aerosol (OA) particles provide useful constraints on OA sources, chemical evolution, and effects. The Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA elemental composition. This study evaluates AMS measurements of atomic oxygen-to-carbon (O : C), hydrogen-to-carbon (H : C), and organic mass-to-organic carbon (OM : OC) ratios, and of carbon oxidation state (OS C) for a vastly expanded laboratory data set of multifunctional oxidized OA standards. For the expanded standard data set, the method introduced by Aiken et al. (2008), which uses experimentally measured ion intensities at all ions to determine elemental ratios (referred to here as "Aiken-Explicit"), reproduces known O : C and H : C ratio values within 20% (average absolute value of relative errors) and 12%, respectively. The more commonly used method, which uses empirically estimated H2O+ and CO+ ion intensities to avoid gas phase air interferences at these ions (referred to here as "Aiken-Ambient"), reproduces O : C and H : C of multifunctional oxidized species within 28 and 14% of known values. The values from the latter method are systematically biased low, however, with larger biases observed for alcohols and simple diacids. A detailed examination of the H2O+, CO+, and CO2+ fragments in the high-resolution mass spectra of the standard compounds indicates that the Aiken-Ambient method underestimates the CO+ and especially H2O+ produced from many oxidized species. Combined AMS–vacuum ultraviolet (VUV) ionization measurements indicate that these ions are produced by dehydration and decarboxylation on the AMS vaporizer (usually operated at 600 °C). Thermal decomposition is observed to be efficient at vaporizer temperatures down to 200 °C. These results are used together to develop an "Improved-Ambient" elemental analysis method for AMS spectra measured in air. The Improved-Ambient method uses specific ion fragments as markers to correct for molecular functionality-dependent systematic biases and reproduces known O : C (H : C) ratios of individual oxidized standards within 28% (13%) of the known molecular values. The error in Improved-Ambient O : C (H : C) values is smaller for theoretical standard mixtures of the oxidized organic standards, which are more representative of the complex mix of species present in ambient OA. For ambient OA, the Improved-Ambient method produces O : C (H : C) values that are 27% (11%) larger than previously published Aiken-Ambient values; a corresponding increase of 9% is observed for OM : OC values. These results imply that ambient OA has a higher relative oxygen content than previously estimated. The OS C values calculated for ambient OA by the two methods agree well, however (average relative difference of 0.06 OS C units). This indicates that OS C is a more robust metric of oxidation than O : C, likely since OS C is not affected by hydration or dehydration, either in the atmosphere or during analysis.

The soot-particle aerosol mass spectrometer (SP-AMS) uses an intra-cavity infrared laser to vaporize refractory black carbon (rBC) containing particles, making the particle beam–laser beam overlap critical in determining the collection efficiency (CE) for rBC and associated non-refractory particulate matter (NR-PM). This work evaluates the ability of the SP-AMS to quantify rBC and NR-PM mass in internally mixed particles with different thicknesses of organic coating. Using apparent relative ionization efficiencies for uncoated and thickly coated rBC particles, we report measurements of SP-AMS sensitivity to NR-PM and rBC, for Regal Black, the recommended particulate calibration material. Beam width probe (BWP) measurements are used to illustrate an increase in sensitivity for highly coated particles due to narrowing of the particle beam, which enhances the CE of the SP-AMS by increasing the laser beam–particle beam overlap. Assuming complete overlap for thick coatings, we estimate CE for bare Regal Black particles of 0.6 ± 0.1, which suggests that previously measured SP-AMS sensitivities to Regal Black were underestimated by up to a factor of 2. The efficacy of the BWP measurements is highlighted by studies at a busy road in downtown Toronto and at a non-roadside location, which show particle beam widths similar to, but greater than that of bare Regal Black and coated Regal Black, respectively. Further BWP measurements at field locations will help to constrain the range of CE for fresh and aged rBC-containing particles. The ability of the SP-AMS to quantitatively assess the composition of internally mixed particles is validated through measurements of laboratory-generated organic coated particles, which demonstrate that the SP-AMS can quantify rBC and NR-PM over a wide range of particle compositions and rBC core sizes.

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher's combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches-dichotomizing all observed phenotypes or treating them as continuous variables-could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies.

We have designed and characterized a new inlet and aerodynamic lens for the Aerodyne aerosol mass spectrometer (AMS) that transmits particles between 80 nm and more than 3 μm in vacuum aerodynamic diameter. The design of the inlet and lens was optimized with computational fluid dynamics (CFD) modeling of particle trajectories. Major changes include a redesigned critical orifice holder and valve assembly, addition of a relaxation chamber behind the critical orifice, and a higher lens operating pressure. The transmission efficiency of the new inlet and lens was characterized experimentally with size-selected particles. Experimental measurements are in good agreement with the calculated transmission efficiency.

Lymphocyte- and leukocyte-mediated lymph node (LN) lymphatic sinus growth (lymphangiogenesis) is involved in immune responses and in diseases including cancer and arthritis. We previously discovered a 10.1.1 Ab that recognizes the lymphatic endothelial cell (LEC) surface protein mCLCA1, which is an interacting partner for LFA1 and Mac-1 that mediates lymphocyte adhesion to LECs. Here, we show that 10.1.1 Ab treatment specifically induces LEC proliferation, and influences migration and adhesion in vitro. Functional testing by injection of mice with 10.1.1 Ab but not control hamster Abs identified rapid induction of LN LEC proliferation and extensive lymphangiogenesis within 23 h. BrdU pulse-chase analysis demonstrated incorporation of proliferating LYVE-1-positive LEC into the growing medullary lymphatic sinuses. The 10.1.1 Ab-induced LN remodeling involved coordinate increases in LECs and also blood endothelial cells, fibroblastic reticular cells, and double negative stroma, as is observed during the LN response to inflammation. 10.1.1 Ab-induced lymphangiogenesis was restricted to LNs, as mCLCA1-expressing lymphatic vessels of the jejunum and dermis were unaffected by 23 h 10.1.1 Ab treatment. These findings demonstrate that 10.1.1 Ab rapidly and specifically induces proliferation and growth of LN lymphatic sinuses and stroma, suggesting a key role of mCLCA1 in coordinating LN remodeling during immune responses.

BACKGROUND:Plasminogen activator inhibitor-1 (PAI-1) is induced in airways by virus and may mediate asthmatic airway remodeling. We sought to evaluate if genetic variants and early life lower respiratory infections jointly affect asthma risk. METHODS:We included Latino children, adolescents, and young adults aged 8-21 years (1736 subjects with physician-diagnosed asthma and 1747 healthy controls) from five U.S. centers and Puerto Rico after excluding subjects with incomplete clinical or genetic data. We evaluated the independent and joint effects of a PAI-1 gain of function polymorphism and bronchiolitis / Respiratory Syncytial Virus (RSV) or other lower respiratory infections (LRI) within the first 2 years of life on asthma risk, asthma exacerbations and lung function. RESULTS:RSV infection (OR 9.9, 95%CI 4.9-20.2) and other LRI (OR 9.1, 95%CI 7.2-11.5) were independently associated with asthma, but PAI-1 genotype was not. There were joint effects on asthma risk for both genotype-RSV (OR 17.7, 95% CI 6.3-50.2) and genotype-LRI (OR 11.7, 95% CI 8.8-16.4). A joint effect of genotype-RSV resulted in a 3.1-fold increased risk for recurrent asthma hospitalizations. In genotype-respiratory infection joint effect analysis, FEV1% predicted and FEV1/FVC % predicted were further reduced in the genotype-LRI group (β -2.1, 95% CI -4.0 to -0.2; β -2.0, 95% CI -3.1 to -0.8 respectively). Similarly, lower FEV1% predicted was noted in genotype-RSV group (β -3.1, 95% CI -6.1 to -0.2) with a trend for lower FEV1/FVC % predicted. CONCLUSIONS:A genetic variant of PAI-1 together with early life LRI such as RSV bronchiolitis is associated with an increased risk of asthma, morbidity, and reduced lung function in this Latino population.

Knowledge of the variations of mass concentration, chemical composition and size distributions of submicron aerosols near roadways is of importance for reducing exposure assessment uncertainties in health effects studies. The goal of this study is to deploy and evaluate an Atmospheric Sciences Research Center-Mobile Laboratory (ASRC-ML), equipped with a suite of rapid response instruments for characterization of traffic plumes, adjacent to the Long Island Expressway (LIE) – a high-traffic highway in the New York City Metropolitan Area. In total, four measurement periods, two in the morning and two in the evening were conducted at a location approximately 30 m south of the LIE. The mass concentrations and size distributions of non-refractory submicron aerosol (NR-PM1) species were measured in situ at a time resolution of 1 min by an Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer, along with rapid measurements (down to 1 Hz) of gaseous pollutants (e.g. HCHO, NO2, NO, O3, and CO2, etc.), black carbon (BC), and particle number concentrations and size distributions. Particulate organics varied dramatically during periods with high traffic influences from the nearby roadway. The variations were mainly observed in the hydrocarbon-like organic aerosol (HOA), a surrogate for primary OA from vehicle emissions. The inorganic species (sulfate, ammonium, and nitrate) and oxygenated OA (OOA) showed much smoother variations indicating minor impacts from traffic emissions. The concentration and chemical composition of NR-PM1 also varied differently on different days depending on meteorology, traffic intensity and vehicle types. Overall, organics dominated the traffic-related NR-PM1 composition (>60%) with HOA accounting for a major fraction of OA. The traffic-influenced organics showed two distinct modes in mass-weighted size distributions, peaking at ∼120 nm and 500 nm (vacuum aerodynamic diameter, Dva), respectively. OOA and inorganic species appear to be internally mixed in the accumulation mode peaking at ∼500–600 nm. The enhancement of organics in traffic emissions mainly occurred at ultrafine mode dominated by HOA, with little relation to the OOA-dominated accumulation mode. From Fast Mobility Particle Sizer (FMPS) measurements, a large increase in number concentration at ∼10 nm (mobility number mean diameter, Dm) was also found due to traffic influence; though these particles typically contribute a minor fraction of total particle mass. The observed rapid variations of aerosol chemistry and microphysics may have significant implications for near-highway air pollution characterization and exposure assessments.

Secondary organic aerosol (SOA) and oxidized primary organic aerosol (OPOA) were produced in laboratory experiments from the oxidation of fourteen precursors representing atmospherically relevant biogenic and anthropogenic sources. The SOA and OPOA particles were generated via controlled exposure of precursors to OH radicals and/or O3 in a Potential Aerosol Mass (PAM) flow reactor over timescales equivalent to 1–20 days of atmospheric aging. Aerosol mass spectra of SOA and OPOA were measured with an Aerodyne aerosol mass spectrometer (AMS). The fraction of AMS signal at m/z = 43 and m/z = 44 (f43, f44), the hydrogen-to-carbon (H/C) ratio, and the oxygen-to-carbon (O/C) ratio of the SOA and OPOA were obtained, which are commonly used to characterize the level of oxidation of oxygenated organic aerosol (OOA). The results show that PAM-generated SOA and OPOA can reproduce and extend the observed f44–f43 composition beyond that of ambient OOA as measured by an AMS. Van Krevelen diagrams showing H/C ratio as a function of O/C ratio suggest an oxidation mechanism involving formation of carboxylic acids concurrent with fragmentation of carbon-carbon bonds. Cloud condensation nuclei (CCN) activity of PAM-generated SOA and OPOA was measured as a function of OH exposure and characterized as a function of O/C ratio. CCN activity of the SOA and OPOA, which was characterized in the form of the hygroscopicity parameter κorg, ranged from 8.4×10−4 to 0.28 over measured O/C ratios ranging from 0.05 to 1.42. This range of κorg and O/C ratio is significantly wider than has been previously obtained. To first order, the κorg-to-O/C relationship is well represented by a linear function of the form κorg = (0.18±0.04) ×O/C + 0.03, suggesting that a simple, semi-empirical parameterization of OOA hygroscopicity and oxidation level can be defined for use in chemistry and climate models.

Motivated by the need to develop instrumental techniques for characterizing organic aerosol aging, we report on the performance of the Toronto Photo-Oxidation Tube (TPOT) and Potential Aerosol Mass (PAM) flow tube reactors under a variety of experimental conditions. The PAM system was designed with lower surface-area-to-volume (SA/V) ratio to minimize wall effects; the TPOT reactor was designed to study heterogeneous aerosol chemistry where wall loss can be independently measured. The following studies were performed: (1) transmission efficiency measurements for CO2, SO2, and bis(2-ethylhexyl) sebacate (BES) particles, (2) H2SO4 yield measurements from the oxidation of SO2, (3) residence time distribution (RTD) measurements for CO2, SO2, and BES particles, (4) aerosol mass spectra, O/C and H/C ratios, and cloud condensation nuclei (CCN) activity measurements of BES particles exposed to OH radicals, and (5) aerosol mass spectra, O/C and H/C ratios, CCN activity, and yield measurements of secondary organic aerosol (SOA) generated from gas-phase OH oxidation of m-xylene and α-pinene. OH exposures ranged from (2.0 ± 1.0) × 1010 to (1.8 ± 0.3) × 1012 molec cm−3 s. Where applicable, data from the flow tube reactors are compared with published results from the Caltech smog chamber. The TPOT yielded narrower RTDs. However, its transmission efficiency for SO2 was lower than that for the PAM. Transmission efficiency for BES and H2SO4 particles was size-dependent and was similar for the two flow tube designs. Oxidized BES particles had similar O/C and H/C ratios and CCN activity at OH exposures greater than 1011 molec cm−3 s, but different CCN activity at lower OH exposures. The O/C ratio, H/C ratio, and yield of m-xylene and α-pinene SOA was strongly affected by reactor design and operating conditions, with wall interactions seemingly having the strongest influence on SOA yield. At comparable OH exposures, flow tube SOA was more oxidized than smog chamber SOA, possibly because of faster gas-phase oxidation relative to particle nucleation. SOA yields were lower in the TPOT than in the PAM, but CCN activity of flow-tube-generated SOA particles was similar. For comparable OH exposures, α-pinene SOA yields were similar in the PAM and Caltech chambers, but m-xylene SOA yields were much lower in the PAM compared to the Caltech chamber.

We report the first measurements of particulate lead (Pb) from Aerodyne Aerosol Mass Spectrometers, which were deployed in and around Mexico City during the Megacity Initiative: Local and Global Research Observations (MILAGRO)/Mexico City Metropolitan Area 2006 (MCMA-2006) field campaigns. The high resolution mass spectrometer of one of the AMS instruments (HR-AMS) and the measured isotopic ratios unequivocally prove the detection of Pb in ambient particles. A substantial fraction of the lead evaporated slowly from the vaporizer of the instruments, which is indicative of species with low volatility at 600 °C. A model was developed in order to estimate the ambient particulate Pb entering the AMS from the signals in the "open" and the "closed" (or "background") mass spectrum modes of the AMS. The model suggests the presence of at least two lead fractions with ~25% of the Pb signal exhibiting rapid evaporation (1/e decay constant, τ3)2 particles, we estimated that the Pb ionization efficiency relative to nitrate (RIEPb) is 0.5. Comparison of time series of AMS Pb with other measurements carried out at the T0 supersite during MILAGRO (using Proton Induced X-ray Emission (PIXE), Inductively-Coupled Plasma Mass Spectrometry (ICP-MS) and single-particle counts from an Aerosol Time-of-Fight Mass Spectrometer (ATOFMS)) shows similar levels (for PIXE and ICP-MS) and substantial correlation. During part of the campaign, sampling at T0 was alternated every 10 min with an Aerosol Concentrator, which enabled the detection of signals for PbCl+ and PbS+ ions. PbS+ displays the signature of a slowly evaporating species, while PbCl+ appears to arise only from fast evaporation, which is likely due to the higher vapor pressure of the compounds generating PbCl+. This is consistent with the evaporation model results. Levels of particulate Pb measured at T0 were similar to previous studies in Mexico City. Pb shows a diurnal cycle with a maximum in the early morning, which is typical of primary urban pollutants. Pb shows correlation with Zn, consistent with previous studies, while the sources of Pb appear to be at least partially disjoint from those of particulate chloride. Back trajectory analysis of the T0 Pb data suggests the presence of sources inside the urban area SSW and N of T0, with different chemical forms of Pb being associated with different source locations. High signals due to particulate lead were also detected in the PEMEX site; again, no correlation between Pb and chloride plumes was observed, suggesting mostly different sources for both species.

Multi-marker approaches have received a lot of attention recently in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene-, gene-set- and pathway-based association tests are increasingly being viewed as useful supplements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants. A major drawback of single-marker based methods is that they do not look at the joint effects of multiple genetic variants which individually may have weak or moderate signals. Here, we describe novel tests for multi-marker association analyses that are based on phenotype predictions obtained from machine learning algorithms. Instead of assuming a linear or logistic regression model, we propose the use of ensembles of diverse machine learning algorithms for prediction. We show that phenotype predictions obtained from ensemble learning algorithms provide a new framework for multi-marker association analysis. They can be used for constructing tests for the joint association of multiple variants, adjusting for covariates and testing for the presence of interactions. To demonstrate the power and utility of this new approach, we first apply our method to simulated SNP datasets. We show that the proposed method has the correct Type-1 error rates and can be considerably more powerful than alternative approaches in some situations. Then, we apply our method to previously studied asthma-related genes in 2 independent asthma cohorts to conduct association tests.

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values